Instantaneous-Angular-Speed-Based Synchronous Averaging Tool for Bearing Outer Race Fault Diagnosis
Xin Chen, Yu Guo, Jing Na
Abstract
Synchronous averaging (SA) is a powerful signal processing tool to enhance the feature of interesting periodic events by suppressing nonsynchronous components. However, the features related to the rolling element bearing (REB) fault may not be effectively enhanced by SA under random slip conditions. To address this issue, two instantaneous angular speed (IAS)-based synchronous averaging frameworks are proposed in this article. Then, an improved negentropy indicator is proposed to characterize the richness of the REB fault information. Additionally, based on the estimation feature of the IAS signal, the effects of the encoder resolution and structure damping factor on the waveform related to the faulty REB are studied, respectively. Simulation and experiment results show that the proposed schemes can be used to enhance the feature of the REB fault under random slip conditions.